With the development and application of the Third Generation (3G) technology of mobile communications, it has become more and more important to get the downlink channel information at the transmitting end in a timely and precise manner, because currently available spectrum resources are becoming increasingly scarce.
Specifically speaking, in order to enhance utilization ratios of spectrums and power under the increasing scarcity of spectrum resources, it is necessary to pre-encode signals at the transmitting end for rational assignment to users of such resources as carriers, bits and power.
For a point-to-point single-user system, pre-encoding at the transmitting end may improve the Bit Error Rate (BER) performance of the system and simplify signal processing at the receiving side. For a downlink multi-user Space Division Multiple Access (SDMA) system, pre-encoding of signals at the transmitting end may effectively eliminate interferences among multiple users at the transmitting end completely or partially, thus reducing the load of signal processing at the receiving side and significantly enhancing downlink capacity of the system. As for an Orthogonal Frequency Division Multiple Access (OFDMA) system, rational assignment of carriers, bits and power may improve overall speed of the system and decrease transmit power.
In view of the above, in order to most possibly improve performance of the system from limited system resources such as limited time slot or limited frequency band, it is essential to meet the condition that the transmitting end can learn the downlink channel information precisely. As should be pointed out, most of the associated solutions in the 3G system employ the frequency division duplex (FDD) mode, and there is no reciprocity between uplink and downlink channels in the FDD mode.
Under such circumstances, it's necessary to establish an effective mechanism for feeding back downlink channel information (DL-CSI), so as to feedback the downlink channel information to the transmitting end in a timely and reliable manner.
Several conventional mechanisms for feeding back channel information, as well as defects inherent therein, are presented below.
The first one is a codebook mechanism for feeding back channel information by constructing a codebook, where the channel information is detected at the receiving side and then vector-quantized to search for the codebook to obtain a codebook number, and the codebook number is fed back to the transmitting end. Although this mode reduces the amount of feedback, its defects rest in greatly reducing feedback precision and increasing processing complexity of the receiving side.
The second one is a channel quality indicator (CQI) mechanism for feeding back channel information, where channel information is detected at the receiving side, a proper Modulation and Coding Scheme (MCS) is selected according to the channel information, and the CQI value is fed back to the transmission terminal. Subsequently, the transmitting end adjusts the MCS according to the CQI value. Although this mode likewise reduces the amount of feedback, it still contains the defects such as low feedback precision, merely coarse description of channel quality, and incapability of reflecting specifics of the channel information.
The third one is a vector-quantization plus coding method of Direct Channel Information Feedback (DCFB), where channel information is sent, either directly or after having been vector-quantized and coded, to the transmitting end. Like all those in the current methods for feeding back channel information, defect of this mode lies in its separate occupation on a certain time slot or frequency band, thus leading to occupation on valuable uplink system resources.
In short, defects commonly existed in all currently available methods for feeding back channel information lie in the necessity of separate occupation on a certain time slot or frequency band, and such occupation consumes valuable uplink system resources and hence cost in feedback is relatively high. Although the first and second methods as discussed above can reduce consumption of system resources through reduction of the amount of feedback, they are nonetheless insufficient in precision.